ATMS和CrIS卫星资料同化对青藏高原天气预报的影响
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摘要
利用WRF模式和GSI同化系统同化美国最新一代的ATMS和Cr IS卫星资料,探讨卫星辐射资料同化对青藏高原天气要素预报准确性的影响。进行了四组试验模拟,即无资料同化的控制试验(CTRL)和三组同化试验,三组同化试验分别为:只用常规观测资料进行同化(CONV)、常规观测资料和ATMS卫星资料同化(ATMS)、常规观测资料和Cr IS卫星资料同化(CRIS)。分析了2015年1月及7月的温度场、相对湿度场和风场的预报能力,除了分析近地表2 m温度场、2 m相对湿度场及10 m风场外,也分析了高地形区域以及低地形区域不同高度层上气象要素的预报能力。结果表明:ATMS和CRIS同化对青藏高原天气要素预报效果改进并不具有普遍性,ATM S同化试验可以有效的增进7月低地形区域的2 m温度场、7月高地形区域2 m相对湿度场以及1月高地形区域10 m风场的24 h、48 h预报能力;CRIS同化对1月高地形区域2 m温度场24 h预报、1月与7月高地形区域10 m风场24 h与48 h预报有改善效果。就垂直分层来讨论,CRIS同化试验不管在哪个高度分层都无法有效地改进模式预报能力,ATMS同化试验则在不同分层、不同变量场有着不一样的预报效果。资料同化后温度场预报主要的误差来源是系统性误差,而相对湿度场和风场在同化后主要误差是由非系统性误差造成的。整体上ATMS同化试验效果优于CRIS同化试验。
The impact of ATMS and Cr IS data assimilation on weather forecasts over the Qinghai-Tibetan Plateau investigated by using NOAA 's Gridpoint Statistical Interpolation( GSI) data assimilation system and NCAR's Advanced Research Weather Research and Forecasting( ARW-WRF) regional model. The experiment was designed with 4 parts: A control experiment( CTRL) and three data assimilation experiments with different data sets,including conventional data only( CONV),a combination of conventional and ATMS satellite data( ATMS),and a combination of conventional and Cr IS satellite data( CRIS). The 2 m temperature( T),2 m relative humidity( RH) and 10 m wind speed( WS) in January and July 2015 were evaluated to investigate the weather forecast ability. Furthermore,those variables in different vertical layers over the terrain were also analyzed to improve the forecast results. The simulation results showed that the improvement of three data assimilation experiments was not general. The forecast ability of 10 m WS in January and the 2 m RH in July could be modified by assimilating ATMS over high-elevation region,while 2 m T prognosis could be rectified over low-elevation region. CRIS showed a good performance over high-elevation region for 24 h 2 m T prediction in July. Meanwhile,CRIS could also improve the prediction accuracy of 10 m WS over high-elevation region in both January and July.Considering the vertical stratification,the CRIS data assimilation had a negative contribution in all vertical layers while ATMS data assimilation had different forecast accuracy in different vertical layers and variables. The forecast error in T was typically caused by the systematic error,which was controlled by the physical representation within the model. In contrast,the inaccuracies in the RH and WS forecasts were dominated by nonsystematic errors,derived from the random inadequacies of the initial conditions. In summary,the overall improvement of ATMS data assimilation over the Qinghai-Tibetan Plateau is better than the improvement of CRIS data assimilation.
The impact of ATMS and Cr IS data assimilation on weather forecasts over the Qinghai-Tibetan Plateau investigated by using NOAA 's Gridpoint Statistical Interpolation( GSI) data assimilation system and NCAR's Advanced Research Weather Research and Forecasting( ARW-WRF) regional model. The experiment was designed with 4 parts: A control experiment( CTRL) and three data assimilation experiments with different data sets,including conventional data only( CONV),a combination of conventional and ATMS satellite data( ATMS),and a combination of conventional and Cr IS satellite data( CRIS). The 2 m temperature( T),2 m relative humidity( RH) and 10 m wind speed( WS) in January and July 2015 were evaluated to investigate the weather forecast ability. Furthermore,those variables in different vertical layers over the terrain were also analyzed to improve the forecast results. The simulation results showed that the improvement of three data assimilation experiments was not general. The forecast ability of 10 m WS in January and the 2 m RH in July could be modified by assimilating ATMS over high-elevation region,while 2 m T prognosis could be rectified over low-elevation region. CRIS showed a good performance over high-elevation region for 24 h 2 m T prediction in July. Meanwhile,CRIS could also improve the prediction accuracy of 10 m WS over high-elevation region in both January and July.Considering the vertical stratification,the CRIS data assimilation had a negative contribution in all vertical layers while ATMS data assimilation had different forecast accuracy in different vertical layers and variables. The forecast error in T was typically caused by the systematic error,which was controlled by the physical representation within the model. In contrast,the inaccuracies in the RH and WS forecasts were dominated by nonsystematic errors,derived from the random inadequacies of the initial conditions. In summary,the overall improvement of ATMS data assimilation over the Qinghai-Tibetan Plateau is better than the improvement of CRIS data assimilation.
引文
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M c Nally A P,Derber J C,Wu W,et al.2000.The use of TOVS level-1b radiances in the NCEP SSI analysis system[J].Quart J Roy M eteor Soc,126(563):689-724.
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M urphy A H.1988.Skill scores based on the mean square error and their relationships to the correlation coefficient[J].M on Wea Rev,116(12):2417-2424.
Nutter P A,M anobianco J.1999.Evaluation of the 29-km Eta M odel.Part I:Objective verification at three selected stations[J].Wea Forecasting,14(1):5-17.
Sasaki Y.1958.An objective analysis based on the variational method[J].J Meteor Soc Japan.Ser.II,36(3):77-88.
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Zou X,Lin L,Weng F.2014.Absolute calibration of ATM S upper level temperature sounding channels using GPS RO observations[J].Geoscience and Remote Sensing,IEEE Transactions on,52(2):1397-1406.
蔡则帅.2015.NPP-ATMS卫星微波资料在WRFDA中的直接同化试验研究[D].南京:南京信息工程大学,19-62.Cai Zeshuai.2015.Direct assimilation study on NPP-ATM S microw ave observation in WRFDA[D].Nanjing:Nanjing University of Information Science&Technology,19-62.
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何光碧,彭俊,屠妮妮.2015.基于高分辨率地形数据的模式地形构造与数值试验[J].高原气象,34(4):910-922.He Guangbi,Peng Jun,Tu Nini.2015.Terrain construction and experiment for numerical model based on high resolution terrain data[J].Plateau M eteor,34(4):910-922.DOI:10.7522/j.issn.1000-0534.2014.00022.
何由,阳坤,姚檀栋,等.2012.基于WRF模式对青藏高原一次强降水的模拟[J].高原气象,31(5):1183-1191.He You,Yang Kun,Yao Tandong,et al.2012.Numerical simulation of a heavy precipitation in Qinghai-Xizang Plateau based on WRF model[J].Plateau M eteor,31(5):1183-1191.
焦彦军,吴声金,钱正安.1991.青藏高原及其邻近地区温压湿场的时空统计特征及其应用[J].高原气象,10(1):13-25.Jiao Yanjun,Wu shengjin,Qian Zheng’an.1991.Temporary and space statistic characteristics of aerological geopotential,temperature and dew-point temperature fields over Qinghai-Xizang Plateau and Their Applications[J].Plateau M eteor,10(1):13-25.
闵爱荣,廖移山,王晓芳,等.2009.ATOVS资料的变分同化对一次暴雨过程预报的影响分析[J].热带气象学报,25(3):314-320.M in Airong,Liao Yishan,Wang Xiaofang,et al.2009.Analyzing the effect of variational data assimilation of satellite radiance on a heavy rain[J].J Trop M eteor,25(3):314-320.
彭世球,徐祥德,施晓晖,等.2008.“世界屋脊”大地形坡面探测同化信息对下游天气的预警效应[J].科学通报,53(24):3134-3138.Peng Shiqiu,Xu Xiangde,Shi Xiaohui,et al.2008.The role of observations used data assimilation from Tibetan Plateau slope[J].Chinese Sci Bull,53(24):3134-3138.
钱正安,焦彦军.1997.青藏高原气象学的研究进展和问题[J].地球科学进展,12(3):207-216.Qian Zheng’an,Jiao Yanjun.1997.Advances and problems on Qinghai-Xizang Plateau meteorology research[J].Adv Earth Sci,12(3):207-216.
王曼,孙绩华,赵韬,等.2013.青藏高原东缘GPS水汽资料对暴雨模拟的影响分析[J].高原山地气象研究,33(4):25-29.Wang M an,Sun Jihua,Zhao Tao,et al.2013.Assimilation test and analysis of the GPS data from the eastern margin of Tibetan Plateau in the rainstorm simulation[J].Plateau M ountain M eteor Res,33(4):25-29.
吴泽,范广洲,周定文,等.2014.基于WRF模式的雅安暴雨数值模拟研究[J].高原气象,33(5):1332-1340.Wu Ze,Fan Guangzhou,Zhou Dingw en,et al.2014.Numerical simulation of the rainstorm process in Ya’an based on WRF model[J].Plateau M eteor,33(5):1332-1340.DOI:10.7522/j.issn.1000-0534.2013.00084.
姚昊,潘晓滨,臧增亮.2008.一次鄂西地区暴雨过程中地形敏感性试验研究[J].气象与环境学报,24(5):61-66.Yao Hao,Pan Xiaobin,Zang Zengliang.2008.Experiments on terrain sensitivity to a heavy rainstorm process in w estern Hubei province[J].J M eteor Environ,24(5):61-66.
叶笃正,顾震潮.1955.西藏高原对于东亚大气环流及中国天气的影响[J].科学通报,6(1):28-33.Ye Duzheng,Gu Zhenchao.1955.Impact of Xizang Plateau on East Asia atmospheric circulation and w eather in China[J].Chinese Sci Bull,6(1):28-33.
殷梦涛,邹晓蕾.2015.极轨气象卫星高光谱红外探测仪简介[J].气象科技进展,5(1):29-39.Yin Mengtao,Zou Xiaolei.2015.An introduction to hyper-spectral infrared sounders onboard polarorbiting meteorological satellites[J].Adv M eteor Sci Technol,5(1):29-39.
张飞民,王澄海.2014.利用WRF-3DVAR同化常规观测资料对近地层风速预报的改进试验[J].高原气象,33(3):675-685.Zhang Feimin,Wang Chenghai.2014.Experiment of surface-layer w ind forecast improvement by assimilating conventional data w ith WRF-3DVAR[J].Plateau M eteor,33(3):675-685.DOI:10.7522/j.issn.1000-0534.2012.00198.
张利红,李跃清,秦宁生,等.2011.青藏高原坡面观测信息对我国夏季降水预报的作用[J].气象,37(10):1233-1240.Zhang Lihong,Li Yueqing,Qin Ningsheng,et al.2011.The role of observations from Tibetan Plateau slope in summer rainfall NWP in China[J].M eteor M on,37(10):1233-1240.
张镱锂,李炳元,郑度.2002.论青藏高原范围与面积[J].地理研究,21(1):1-8.Zhang Yili,Li Bingyuan,Zheng Du.2002.Adiscussion on the boundary and area of the Tibetan Plateau in China[J].Acta Geographica Sinica,21(1):1-8.
周昊.2012.GSI三维变分同化技术在降水预报中的应用[D].南京:南京信息工程大学,10-19.Zhou Hao.2012.Application of GSI-3DVAR technique on precipitation forecast[D].Nanjing:Nanjing University of Information Science&Technology,10-19.
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Bao Y,Xu J,Pow ell Jr A M,et al.2015.Impacts of AM SU-A,M HSand IASI data assimilation on temperature and humidity forecasts w ith GSI-WRF over the w estern United States[J].Atmospheric M easurement Techniques,8(10):4231-4242.
Derber J C,Parrish D F,Lord S J.1991.The new global operational analysis system at the National M eteorological Center[J].Wea Forecasting,6(4):538-547.
Derber J.2012.Progress and plans for the Environmental M odeling Center’s(EM C)Gridpoint Statistical Interpolation(GSI)development[M/OL].1-47.https://w w w.jcsda.noaa.gov/documents/seminardocs/2012/Derber20120321.pdf.[2016-04-05].
Eyre J R.1992.A bias correction scheme for simulated TOVS brightness temperatures[M].European Centre for M edium-Range Weather Forecasts,28.
Liu Q,Weng F.2006.Detecting the w arm core of a hurricane from the special sensor microw ave imager sounder[J].Geophys Res Lett,33(6):863-883.
M c Nally A P,Derber J C,Wu W,et al.2000.The use of TOVS level-1b radiances in the NCEP SSI analysis system[J].Quart J Roy M eteor Soc,126(563):689-724.
M oncet J L,Uymin G,Snell H E.2004.Atmospheric radiance modeling using the optimal spectral sampling(OSS)method[C]//Defense and Security.International Society for Optics and Photonics,368-374.
M urphy A H.1988.Skill scores based on the mean square error and their relationships to the correlation coefficient[J].M on Wea Rev,116(12):2417-2424.
Nutter P A,M anobianco J.1999.Evaluation of the 29-km Eta M odel.Part I:Objective verification at three selected stations[J].Wea Forecasting,14(1):5-17.
Sasaki Y.1958.An objective analysis based on the variational method[J].J Meteor Soc Japan.Ser.II,36(3):77-88.
Wang B,Zou X,Zhu J.2000.Data assimilation and its applications[J].Proceedings of the National Academy of Sciences,97(21):11143-11144.
Wang L,Han Y,Tremblay D,et al.2012.Inter-comparison of NPP/Cr IS radiances w ith VIIRS AIRS and IASI:a post-launch calibration assessment[C]//Earth Observing M issions and Sensors:Development,Implementation,and Characterization II,8528:85280J-85280J-7.
Xu J,Rugg S,Byerle L,et al.2009.Weather forecasts by the WRF-ARW model w ith the GSI data assimilation system in the complex terrain areas of southw est Asia[J].Wea Forecasting,24(4):987-1008.
Yang J,Duan K,Wu J,et al.2015.Effect of data assimilation using WRF-3DVAR for heavy rain prediction on the northeastern edge of the Tibetan Plateau[J].Adv M eteor,15:1-14.
Zapotocny T H,Jung J A,Le M arshall J F,et al.2008.A tw o-season impact study of four satellite data types and raw insonde data in the NCEP Global data assimilation system[J].Wea Forecasting,23(1):80-100.
Zhou H,Gómez-Hernández J J,Franssen H J H,et al.2011.An approach to handling non-gaussianity of parameters and state variables in ensemble Kalman filtering[J].Advances in Water Resources,34(7):844-864.
Zou X,Lin L,Weng F.2014.Absolute calibration of ATM S upper level temperature sounding channels using GPS RO observations[J].Geoscience and Remote Sensing,IEEE Transactions on,52(2):1397-1406.
蔡则帅.2015.NPP-ATMS卫星微波资料在WRFDA中的直接同化试验研究[D].南京:南京信息工程大学,19-62.Cai Zeshuai.2015.Direct assimilation study on NPP-ATM S microw ave observation in WRFDA[D].Nanjing:Nanjing University of Information Science&Technology,19-62.
董佩明,刘健文,刘桂青,等.2014.ATMS卫星资料的同化应用及与AMSUA/MHS的比较研究[J].热带气象学报,30(4):623-632.Dong Peiming,Liu Jianw en,Liu Guiqing,et al.2014.Study on the assimilation of ATM S satellite data and comparison w ith AM SUA/M HS[J].J Trop M eteor,30(4):623-632.
何光碧,彭俊,屠妮妮.2015.基于高分辨率地形数据的模式地形构造与数值试验[J].高原气象,34(4):910-922.He Guangbi,Peng Jun,Tu Nini.2015.Terrain construction and experiment for numerical model based on high resolution terrain data[J].Plateau M eteor,34(4):910-922.DOI:10.7522/j.issn.1000-0534.2014.00022.
何由,阳坤,姚檀栋,等.2012.基于WRF模式对青藏高原一次强降水的模拟[J].高原气象,31(5):1183-1191.He You,Yang Kun,Yao Tandong,et al.2012.Numerical simulation of a heavy precipitation in Qinghai-Xizang Plateau based on WRF model[J].Plateau M eteor,31(5):1183-1191.
焦彦军,吴声金,钱正安.1991.青藏高原及其邻近地区温压湿场的时空统计特征及其应用[J].高原气象,10(1):13-25.Jiao Yanjun,Wu shengjin,Qian Zheng’an.1991.Temporary and space statistic characteristics of aerological geopotential,temperature and dew-point temperature fields over Qinghai-Xizang Plateau and Their Applications[J].Plateau M eteor,10(1):13-25.
闵爱荣,廖移山,王晓芳,等.2009.ATOVS资料的变分同化对一次暴雨过程预报的影响分析[J].热带气象学报,25(3):314-320.M in Airong,Liao Yishan,Wang Xiaofang,et al.2009.Analyzing the effect of variational data assimilation of satellite radiance on a heavy rain[J].J Trop M eteor,25(3):314-320.
彭世球,徐祥德,施晓晖,等.2008.“世界屋脊”大地形坡面探测同化信息对下游天气的预警效应[J].科学通报,53(24):3134-3138.Peng Shiqiu,Xu Xiangde,Shi Xiaohui,et al.2008.The role of observations used data assimilation from Tibetan Plateau slope[J].Chinese Sci Bull,53(24):3134-3138.
钱正安,焦彦军.1997.青藏高原气象学的研究进展和问题[J].地球科学进展,12(3):207-216.Qian Zheng’an,Jiao Yanjun.1997.Advances and problems on Qinghai-Xizang Plateau meteorology research[J].Adv Earth Sci,12(3):207-216.
王曼,孙绩华,赵韬,等.2013.青藏高原东缘GPS水汽资料对暴雨模拟的影响分析[J].高原山地气象研究,33(4):25-29.Wang M an,Sun Jihua,Zhao Tao,et al.2013.Assimilation test and analysis of the GPS data from the eastern margin of Tibetan Plateau in the rainstorm simulation[J].Plateau M ountain M eteor Res,33(4):25-29.
吴泽,范广洲,周定文,等.2014.基于WRF模式的雅安暴雨数值模拟研究[J].高原气象,33(5):1332-1340.Wu Ze,Fan Guangzhou,Zhou Dingw en,et al.2014.Numerical simulation of the rainstorm process in Ya’an based on WRF model[J].Plateau M eteor,33(5):1332-1340.DOI:10.7522/j.issn.1000-0534.2013.00084.
姚昊,潘晓滨,臧增亮.2008.一次鄂西地区暴雨过程中地形敏感性试验研究[J].气象与环境学报,24(5):61-66.Yao Hao,Pan Xiaobin,Zang Zengliang.2008.Experiments on terrain sensitivity to a heavy rainstorm process in w estern Hubei province[J].J M eteor Environ,24(5):61-66.
叶笃正,顾震潮.1955.西藏高原对于东亚大气环流及中国天气的影响[J].科学通报,6(1):28-33.Ye Duzheng,Gu Zhenchao.1955.Impact of Xizang Plateau on East Asia atmospheric circulation and w eather in China[J].Chinese Sci Bull,6(1):28-33.
殷梦涛,邹晓蕾.2015.极轨气象卫星高光谱红外探测仪简介[J].气象科技进展,5(1):29-39.Yin Mengtao,Zou Xiaolei.2015.An introduction to hyper-spectral infrared sounders onboard polarorbiting meteorological satellites[J].Adv M eteor Sci Technol,5(1):29-39.
张飞民,王澄海.2014.利用WRF-3DVAR同化常规观测资料对近地层风速预报的改进试验[J].高原气象,33(3):675-685.Zhang Feimin,Wang Chenghai.2014.Experiment of surface-layer w ind forecast improvement by assimilating conventional data w ith WRF-3DVAR[J].Plateau M eteor,33(3):675-685.DOI:10.7522/j.issn.1000-0534.2012.00198.
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